I have approximate answers and possible beliefs, in different degrees of certainty, about different things. But I'm not absolutely sure of anything and of many things I don't know anything about, such as whether it means anything to ask why we're here and what the question might mean. Richard Feynman During an interview in BBC's Horizon program (1981)

Last year, before doing the nba preseason predictions,  I told you all that I was going to get this wrong. There seemed to be significant disconnect between what people thought they know and what the numbers actually said. Not only that but I knew that as with every prediction model there was absolutely no way I was going to get everything right.

Making predictions is a thankless exercise, but I love a challenge. Shall we look at how I actually did last year?

  • An average absolute error of 6 wins. It goes down to less than 5 if I ignore the injury disasters (Minnesota, New Orleans and Philly) and the Rudy Gay trade (Memphis)
  • 23 teams finished within 8 wins of the prediction. There were 2 predictions on the high side and 5 on the low side.
  • I predicted 13 of 16 Playoff teams.
  • I predicted the finals matchup. I came within a ridiculous Ray Allen three of calling that series as well.
  • I did very well last year.

But! We're going to see if we can match and improve on that this year. You see, rather than doing every team in one post, we're going to do a detailed breakdown of all 30 NBA teams.  You'll probably agree with some of our predictions, and you'll be shocked and outraged by others, but most of all, we hope that you'll be entertained.

We wouldn't mind if you told 100 of your closest friends about it, either.

Let's go over the basics for the projections first. To get to this point I had to:

Using all that information, I'm able to model player productivity for the coming year and create a win model for each team based on the following simple equation:

TeamWins = WinsPrevious WinsLost WinsGained PlayerGrowth PosADJ


  • WinsPrevious is the expected wins for previous year (This is the games the team would have been expected to win based on their Point Margin per 48 minutes last year).
  • WinsLost are the wins lost from losing productive players (i.e. wins lost to free agency, or retirement)
  • WinsGained are the wins added to the roster. These are the wins gained through acquiring free agents or draft picks.
  • PlayerGrowth is the change in player production, either a growth or a decline. These are the wins lost or gained through rotation/minute adjustments, and the progress of Father Time, which will be beneficial to the young folks, and pretty rough on the older folks.
  • PosADJ is the size and/or position adjustment based on projected rosters.

I throw this goodness in a bowl, crank the mixer up to "puree", and generate projections for each team. One new wrinkle for this year is that I've refined my variability projection for the model. This means that I should be able to more accurately forecast the likelihood of a given win total for each team.

Now, where should we start? Well, how about the bottom? Click through to read our first preview!

Want even more information? We've got the preseason data crunched as well.

Here's how the NBA looked to use right before tip off. There are upsets and surprises to be sure, but from where?

As a public service, Arturo was kind enough to update all the rosters post Gortat trade, re-run the Sim and include the playoffs. See the results here

Portland Trail Blazers 32 - 13 .711
Oklahoma City Thunder 22 - 21 .512
Denver Nuggets 18 - 25 .419
Utah Jazz 16 - 28 .364
Minnesota Timberwolves 7 - 35 .167
Golden State Warriors 35 - 6 .854
Los Angeles Clippers 29 - 14 .674
Phoenix Suns 26 - 19 .578
Sacramento Kings 16 - 27 .372
Los Angeles Lakers 12 - 32 .273
Memphis Grizzlies 31 - 12 .721
Dallas Mavericks 30 - 14 .682
Houston Rockets 30 - 14 .682
San Antonio Spurs 28 - 17 .622
New Orleans Pelicans 22 - 21 .512
Chicago Bulls 29 - 16 .644
Cleveland Cavaliers 24 - 20 .545
Milwaukee Bucks 22 - 21 .512
Detroit Pistons 17 - 27 .386
Indiana Pacers 15 - 30 .333
Toronto Raptors 28 - 15 .651
Brooklyn Nets 18 - 26 .409
Boston Celtics 15 - 26 .366
New York Knicks 8 - 37 .178
Philadelphia 76ers 8 - 36 .182
Atlanta Hawks 36 - 8 .818
Washington Wizards 29 - 15 .659
Miami Heat 19 - 24 .442
Charlotte Hornets 19 - 26 .422
Orlando Magic 15 - 31 .326